Energy-Efficient Dynamic Workflow Scheduling in Cloud Environments Using Deep Learning
Dynamic workflow scheduling in cloud environments is a challenging task due to task dependencies, fluctuating workloads, resource variability, and the need to balance makespan and energy consumption. This study presents a novel scheduling framework that integrates Graph Neural Networks (GNNs) with D...
| المؤلفون الرئيسيون: | , |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
MDPI AG
2025-02-01
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| سلاسل: | Sensors |
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://www.mdpi.com/1424-8220/25/5/1428 |